Pingshi Yu

dblp:292/2167 · DBLP profile ↗
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3ranked-venue papers
2as first author
3since 2021 · last 2025
0000-0002-4998-4878ORCID · corroborated

Domains — the database's venue-derived domains; a paper can count in several

Software engineering, systems software and programming languages · 3 · 2 first-author · 3 since 2021Systems, architecture and hardware · 1 · 1 first-author · 1 since 2021
YearPublicationVenuePosition
2025 Ratte: Fuzzing for Miscompilations in Multi-Level Compilers Using Composable Semantics
Pingshi Yu, Nicolas Wu, Alastair F. Donaldson
ASPLOS (2)1
2023 RustSmith: Random Differential Compiler Testing for Rust
abstract
We present RustSmith, the first Rust randomised program generator for end-to-end testing of Rust compilers. RustSmith generates programs that conform to the advanced type system of Rust, respecting rules related to borrowing and lifetimes, and that are guaranteed to yield a well-defined result. This makes RustSmith suitable for differential testing between compilers or across optimisation levels. By applying RustSmith to a series of versions of the official Rust compiler, rustc, we show that it can detect insidious historical bugs that evaded detection for some time. We have also used RustSmith to find previously-unknown bugs in an alternative Rust compiler implementation, mrustc. In a controlled experiment, we assess statement and mutation coverage achieved by RustSmith vs. the rustc optimisation test suite.
Pingshi Yu, Alastair F. Donaldson
ISSTA2
2023 Reasoning about MLIR Semantics through Effects and Handlers
abstract
MLIR is a novel framework for developing intermediate representations (IRs) of compilers. At its core, MLIR is a framework for the specification of syntax fragments (dialects) and optimisations, which can be combined à−la−carte to form customised IRs. Through this, MLIR allows IR abstractions to be shared across different domains. With rapid adoption of MLIR across industry, techniques for formalised semantics which matches the flexibility and extensibility offered by MLIR are urgently needed. We propose a framework for MLIR semantics based on effect handlers, which allows for dialect semantics to be specified in a modular and composable way, parallel to MLIR. We also describe several research directions continuing on from handlers-based MLIR semantics.
Pingshi Yu
ISSTA1